One up-and-coming use case in the Capital Markets that we are excited about is front office real-time risk analytics on streaming market data, to decrease risk by informing traders in real time about potential changes to trading strategies, based on the most up-to-date data possible.

Traditionally, this function has been done post-trade, for compliance and reporting purposes, and to adjust trading strategies. But with today’s move towards Big Data, and the difficult task of processing more and more information faster and faster, many Capital Markets firms have identified a need to perform risk analytics in real time, or near-real time.

How does it work? The combination of UM Cache with B2B-DT handles the tasks of ingesting highly volatile streaming data, and transforming it into any format required by your analytics grid. The result: streaming data is transformed and and risk-analyzed — and available for your applications and traders — as fast as your computing and network platforms will allow.

In our proof-of-concept testing, using EMC Greenplum for the MPP database, we were able to push through 3M messages per second. Similar results should be attainable with any analytics engine, whether you buy or build.